Published on: 2025-06-11 20:39:01
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Alibaba Group has introduced QwenLong-L1, a new framework that enables large language models (LLMs) to reason over extremely long inputs. This development could unlock a new wave of enterprise applications that require models to understand and draw insights from extensive documents such as detailed corporate filings, lengthy financial statements, or complex legal contra
Keywords: l1 long model qwenlong reasoning
Find related items on AmazonPublished on: 2025-06-16 10:10:01
Chinese startup DeepSeek, which caused shockwaves across markets this year, quietly released an upgraded version of its artificial intelligence reasoning model. The company did not make an official announcement, but the upgrade of DeepSeek R1 was released on AI model repository Hugging Face. DeepSeek rose to prominence this year after its free, open-source R1 reasoning model outperformed offerings from rivals including Meta and OpenAI. The low-cost and short time of development shocked global
Keywords: ai deepseek model r1 reasoning
Find related items on AmazonPublished on: 2025-06-17 04:17:56
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Researchers from Meta’s FAIR team and The Hebrew University of Jerusalem have discovered that forcing large language models to “think” less actually improves their performance on complex reasoning tasks. The study released today found that shorter reasoning processes in AI systems lead to more accurate results while significantly reducing computational costs. “In this
Keywords: ai chains performance reasoning shorter
Find related items on AmazonPublished on: 2025-06-18 13:39:11
I built AutoThink, a technique that makes local LLMs reason more efficiently by adaptively allocating computational resources based on query complexity. The core idea: instead of giving every query the same "thinking time," classify queries as HIGH or LOW complexity and allocate thinking tokens accordingly. Complex reasoning gets 70-90% of tokens, simple queries get 20-40%. I also implemented steering vectors derived from Pivotal Token Search (originally from Microsoft's Phi-4 paper) that guid
Keywords: baseline com complexity local reasoning
Find related items on AmazonPublished on: 2025-06-18 18:39:11
I built AutoThink, a technique that makes local LLMs reason more efficiently by adaptively allocating computational resources based on query complexity. The core idea: instead of giving every query the same "thinking time," classify queries as HIGH or LOW complexity and allocate thinking tokens accordingly. Complex reasoning gets 70-90% of tokens, simple queries get 20-40%. I also implemented steering vectors derived from Pivotal Token Search (originally from Microsoft's Phi-4 paper) that guid
Keywords: baseline com complexity local reasoning
Find related items on AmazonPublished on: 2025-06-21 09:09:52
I mostly wrote this post as an excuse to try the freshly-minted and excellent pydantic-evals framework for LLM evaluations but one interesting question that arises when working with Pydantic Models to implement structured output in your AI applications is: What happens if you shuffle the order of fields in your schema? Does it matter if your output type looks like this: class AgentOutput(BaseModel): answer: str reasoning: str or like this: class AgentOutput(BaseModel): reasoning: str answer:
Keywords: answer gpt model reasoning task
Find related items on AmazonPublished on: 2025-06-24 15:00:25
Introduction Traditional AI agents operate through pre-defined reasoning strategies, limiting their ability to respond to unexpected changes or novel inputs. Meta-reasoning, defined as the process by which an agent monitors and adjusts its own reasoning, has emerged as a promising paradigm for overcoming these limitations. Despite strong theoretical foundations, empirical demonstrations of meta-reasoning’s benefits across domains have remained limited until recent years. As the adoption of aut
Keywords: agent agents decision meta reasoning
Find related items on AmazonPublished on: 2025-06-26 16:45:00
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Anthropic released Claude Opus 4 and Claude Sonnet 4 today, dramatically raising the bar for what AI can accomplish without human intervention. The company’s flagship Opus 4 model maintained focus on a complex open-source refactoring project for nearly seven hours during testing at Rakuten — a breakthrough that transforms AI from a quick-response tool into a genuine co
Keywords: ai anthropic claude models reasoning
Find related items on AmazonPublished on: 2025-07-01 15:54:54
When I think about AI, I think about topology. Topology is a big scary math word that basically means 'the study of surfaces'. Imagine you had a surface made of play-doh. You could bend it, or twist it, or stretch it. But as long as you don't rip the play-doh up, or poke a hole through it, you can define certain properties that would remain true regardless of the deformation you apply. Here's an example. Let's say I flatten out my play-doh and then draw a circle on it. I could rotate it, or ben
Keywords: manifold model neural reasoning topology
Find related items on AmazonPublished on: 2025-07-04 03:38:30
Following the web redesign and other changes, Google is introducing a new prompt bar for the Gemini app on Android and iOS. Gemini is going from a pill-shaped text field to a rounded rectangle (even before you enter text). Underneath the “Ask Gemini” field, you get a row of actions, starting with the ‘plus’ menu that’s now much shorter. You just get Camera, Gallery, Files, and Drive in this bottom sheet. Next up are pill-shaped buttons for “Research” and “Canvas.” Tap the three-dot icon in a c
Keywords: code gemini google reasoning redesign
Find related items on AmazonPublished on: 2025-07-12 04:13:46
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Poe‘s latest usage report shows OpenAI and Google strengthening their positions in key AI categories while Anthropic loses ground and specialized reasoning capabilities emerge as a crucial competitive battleground. According to data released today by Poe, a platform offering access to more than 100 AI models, significant market share shifts occurred across all major AI
Keywords: ai generation models reasoning share
Find related items on AmazonPublished on: 2025-07-14 00:36:11
An analysis by Epoch AI, a nonprofit AI research institute, suggests the AI industry may not be able to eke massive performance gains out of reasoning AI models for much longer. As soon as within a year, progress from reasoning models could slow down, according to the report’s findings. Reasoning models such as OpenAI’s o3 have led to substantial gains on AI benchmarks in recent months, particularly benchmarks measuring math and programming skills. The models can apply more computing to problem
Keywords: ai computing epoch models reasoning
Find related items on AmazonPublished on: 2025-07-23 20:00:18
Elyse Betters Picaro / ZDNET Many have dubbed this year "the year of AI agents," as these AI systems that can carry out tasks for users are especially useful for optimizing enterprise workflows. At ServiceNow's annual Knowledge 2025 conference, the company unveiled a new model in partnership with Nvidia to advance AI agents. Apriel Nemotron 15B On Tuesday, ServiceNow and Nvidia launched Apriel Nemotron 15B, a new, open-source reasoning language model (LLM) built to deliver lower latency, lowe
Keywords: ai data model nvidia reasoning
Find related items on AmazonPublished on: 2025-07-25 16:04:14
Artificial intelligence models have long struggled with hallucinations, a conveniently elegant term the industry uses to denote fabrications that large language models often serve up as fact. And judging by the trajectory of the latest "reasoning" models, which the likes of Google and AI have designed to "think" through a problem before answering, the problem is getting worse — not better. As the New York Times reports, as AI models become more powerful, they're also becoming more prone to hal
Keywords: ai hallucinations models openai reasoning
Find related items on AmazonPublished on: 2025-07-30 22:41:29
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Microsoft Research has announced the release of Phi-4-reasoning-plus, an open-weight language model built for tasks requiring deep, structured reasoning. Building on the architecture of the previously released Phi-4, the new model integrates supervised fine-tuning and reinforcement learning to deliver improved performance on benchmarks in mathematics, science, coding,
Keywords: microsoft model phi plus reasoning
Find related items on AmazonPublished on: 2025-07-31 17:02:41
Microsoft continues to add to the conversation by unveiling its newest models, Phi-4-reasoning, Phi-4-reasoning-plus, and Phi-4-mini-reasoning. A new era of AI One year ago, Microsoft introduced small language models (SLMs) to customers with the release of Phi-3 on Azure AI Foundry, leveraging research on SLMs to expand the range of efficient AI models and tools available to customers. Today, we are excited to introduce Phi-4-reasoning, Phi-4-reasoning-plus, and Phi-4-mini-reasoning—marking a
Keywords: ai mini models phi reasoning
Find related items on AmazonPublished on: 2025-07-31 19:23:56
Microsoft launched several new “open” AI models on Wednesday, the most capable of which is competitive with OpenAI’s o3-mini on at least one benchmark. All of the new pemissively licensed models — Phi 4 mini reasoning, Phi 4 reasoning, and Phi 4 reasoning plus — are “reasoning” models, meaning they’re able to spend more time fact-checking solutions to complex problems. They expand Microsoft’s Phi “small model” family, which the company launched a year ago to offer a foundation for AI developers
Keywords: ai microsoft model phi reasoning
Find related items on AmazonPublished on: 2025-08-02 07:33:37
Ever needed a graceful way to say “no”? This tiny API returns random, generic, creative, and sometimes hilarious rejection reasons — perfectly suited for any scenario: personal, professional, student life, dev life, or just because. Built for humans, excuses, and humor. 🚀 API Usage Base URL https://naas.isalman.dev/no Method: GET Rate Limit: 10 requests per minute per IP 🔄 Example Request GET /no ✅ Example Response { "reason" : " This feels like something Future Me would yell at Prese
Keywords: api reasons rejection service start
Find related items on AmazonPublished on: 2025-08-05 10:32:05
Qwen3 is Alibaba's debut into so-called "hybrid reasoning models," which it says combines traditional LLM capabilities with "advanced, dynamic reasoning." Alibaba released the next generation of its open-sourced large language models, Qwen3, on Tuesday — and experts are calling it yet another breakthrough in China's booming open-source artificial intelligence space. In a blog post, the Chinese tech giant said Qwen3 promises improvements in reasoning, instruction following, tool usage and multi
Keywords: alibaba llm models qwen3 reasoning
Find related items on AmazonPublished on: 2025-08-06 04:31:21
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Researchers from UCLA and Meta AI have introduced d1, a novel framework using reinforcement learning (RL) to significantly enhance the reasoning capabilities of diffusion-based large language models (dLLMs). While most attention has focused on autoregressive models like GPT, dLLMs offer unique advantages. Giving them strong reasoning skills could unlock new efficiencies
Keywords: autoregressive d1 dllms models reasoning
Find related items on AmazonPublished on: 2025-08-07 20:43:09
There's a curious contradiction at the heart of today's most capable AI models that purport to "reason": They can solve routine math problems with impressive accuracy, yet when faced with formulating deeper mathematical proofs found in competition-level challenges, they often fail. That's the finding of eye-opening preprint research into simulated reasoning (SR) models, initially listed in March and updated in April, that mostly fell under the news radar. The research serves as an instructive c
Keywords: math models problems proofs reasoning
Find related items on AmazonPublished on: 2025-08-12 16:04:00
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More 2025 was, by many expert accounts, supposed to be the year of AI agents — task-specific AI implementations powered by leading large language and multimodal models (LLMs) like the kinds offered by OpenAI, Anthropic, Google, and DeepSeek. But so far, most AI agents remain stuck as experimental pilots in a kind of corporate purgatory, according to a recent poll conducted
Keywords: ai ragen reasoning reward training
Find related items on AmazonPublished on: 2025-08-15 20:35:16
Over the years, the increasingly ubiquitous use of drones in the United States has raised a lot of privacy concerns. But if a random drone is hovering around your home, what can you do about it? Well, a new bill in Florida’s Senate would let property owners use “reasonable force” against them. The bill aims to expand Florida’s overall restrictions on “Unmanned Aircraft Systems,” redefining no-fly zones to include airports and prisons. But its proposal for property owners is generating the most
Keywords: drones florida property reasonable use
Find related items on AmazonPublished on: 2025-08-16 06:24:37
Recent breakthroughs in reasoning-focused large language models (LLMs) like OpenAI-o1, DeepSeek-R1, and Kimi-1.5 have largely relied on Reinforcement Learning with Verifiable Rewards (RLVR), which replaces human annotations with automated rewards (e.g., verified math solutions or passing code tests) to scale self-improvement. While RLVR enhances reasoning behaviors such as self-reflection and iterative refinement, we challenge a core assumption: Does RLVR actually expand LLMs' reasoning capabil
Keywords: llms models pass reasoning rlvr
Find related items on AmazonPublished on: 2025-08-18 19:43:12
OpenAI’s recently launched o3 and o4-mini AI models are state-of-the-art in many respects. However, the new models still hallucinate, or make things up — in fact, they hallucinate more than several of OpenAI’s older models. Hallucinations have proven to be one of the biggest and most difficult problems to solve in AI, impacting even today’s best-performing systems. Historically, each new model has improved slightly in the hallucination department, hallucinating less than its predecessor. But th
Keywords: mini models o3 openai reasoning
Find related items on AmazonPublished on: 2025-08-19 04:09:44
OpenAI’s recently launched o3 and o4-mini AI models are state-of-the-art in many respects. However, the new models still hallucinate, or make things up — in fact, they hallucinate more than several of OpenAI’s older models. Hallucinations have proven to be one of the biggest and most difficult problems to solve in AI, impacting even today’s best-performing systems. Historically, each new model has improved slightly in the hallucination department, hallucinating less than its predecessor. But th
Keywords: mini models o3 openai reasoning
Find related items on AmazonPublished on: 2025-08-21 04:27:30
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Google has launched Gemini 2.5 Flash, a major upgrade to its AI lineup that gives businesses and developers unprecedented control over how much “thinking” their AI performs. The new model, released today in preview through Google AI Studio and Vertex AI, represents a strategic effort to deliver improved reasoning capabilities while maintaining competitive pricing in the
Keywords: ai google model reasoning thinking
Find related items on AmazonPublished on: 2025-08-21 20:00:00
“We’ve been really pushing on ‘thinking,’” says Jack Rae, a principal research scientist at DeepMind. Such models, which are built to work through problems logically and spend more time arriving at an answer, rose to prominence earlier this year with the launch of the DeepSeek R1 model. They’re attractive to AI companies because they can make an existing model better by training it to approach a problem pragmatically. That way, the companies can avoid having to build a new model from scratch. W
Keywords: model models problem reasoning says
Find related items on AmazonPublished on: 2025-08-21 20:00:00
Yuichiro Chino/Getty Images Just weeks after unveiling Gemini 2.5 Pro, Google is on to its next top-performing model. On Thursday, the company released an "early version" of Gemini 2.5 Flash in preview in the Gemini API, AI Studio, and Vertex AI. The model has a knowledge cutoff of January 2025. It can take text, images, video, and audio prompts, and has a one-million-token context window. Also: Gemini Pro 2.5 is a stunningly capable coding assistant - and a big threat to ChatGPT Google says
Keywords: ai flash gemini google reasoning
Find related items on AmazonPublished on: 2025-08-21 20:03:39
Our Gemini 2.5 models are thinking models, capable of reasoning through their thoughts before responding. Instead of immediately generating an output, the model can perform a "thinking" process to better understand the prompt, break down complex tasks, and plan a response. On complex tasks that require multiple steps of reasoning (like solving math problems or analyzing research questions), the thinking process allows the model to arrive at more accurate and comprehensive answers. In fact, Gemin
Keywords: budget flash model reasoning thinking
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